from sklearn_benchmarks.reporting.hp_match import HpMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = HpMatchReporting(other_library="sklearnex", config="config.yml", log_scale=True)
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time sklearnex. For instance, a speedup of 2 means that sklearnex is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | function | diff_accuracy_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 4 | KNeighborsClassifier_brute_force | predict | 0.067 | 100000 | 1000 | 100 | 3.105810 | 0.045852 | NaN | 0.000258 | 0.003106 | brute | -1 | 5 | 0.743 | 0.226007 | 0.001248 | 0.676 | 13.742109 | 13.742319 |
| 5 | KNeighborsClassifier_brute_force | predict | 1.000 | 100000 | 1 | 100 | 0.024820 | 0.002282 | NaN | 0.000032 | 0.024820 | brute | -1 | 5 | 1.000 | 0.008910 | 0.000214 | 0.000 | 2.785486 | 2.786289 |
| 7 | KNeighborsClassifier_brute_force | predict | 0.103 | 100000 | 1000 | 100 | 2.384116 | 0.005277 | NaN | 0.000336 | 0.002384 | brute | 1 | 100 | 0.846 | 0.229251 | 0.002502 | 0.743 | 10.399586 | 10.400205 |
| 13 | KNeighborsClassifier_brute_force | predict | 0.103 | 100000 | 1000 | 100 | 2.375006 | 0.004540 | NaN | 0.000337 | 0.002375 | brute | 1 | 5 | 0.743 | 0.282499 | 0.000893 | 0.846 | 8.407146 | 8.407188 |
| 16 | KNeighborsClassifier_brute_force | predict | 0.067 | 100000 | 1000 | 100 | 1.251740 | 0.016235 | NaN | 0.000639 | 0.001252 | brute | 1 | 1 | 0.676 | 0.229929 | 0.000688 | 0.743 | 5.444032 | 5.444057 |
| 17 | KNeighborsClassifier_brute_force | predict | 1.000 | 100000 | 1 | 100 | 0.019407 | 0.000194 | NaN | 0.000041 | 0.019407 | brute | 1 | 1 | 0.000 | 0.008780 | 0.000231 | 1.000 | 2.210377 | 2.211141 |
| 22 | KNeighborsClassifier_brute_force | predict | 0.038 | 100000 | 1000 | 2 | 2.963670 | 0.021615 | NaN | 0.000005 | 0.002964 | brute | -1 | 5 | 0.883 | 0.036591 | 0.000125 | 0.845 | 80.994390 | 80.994865 |
| 25 | KNeighborsClassifier_brute_force | predict | 0.004 | 100000 | 1000 | 2 | 2.310522 | 0.001777 | NaN | 0.000007 | 0.002311 | brute | 1 | 100 | 0.887 | 0.038284 | 0.000144 | 0.883 | 60.351726 | 60.352153 |
| 31 | KNeighborsClassifier_brute_force | predict | 0.004 | 100000 | 1000 | 2 | 2.337245 | 0.027438 | NaN | 0.000007 | 0.002337 | brute | 1 | 5 | 0.883 | 0.086500 | 0.002885 | 0.887 | 27.020217 | 27.035245 |
| 34 | KNeighborsClassifier_brute_force | predict | 0.038 | 100000 | 1000 | 2 | 1.113005 | 0.007140 | NaN | 0.000014 | 0.001113 | brute | 1 | 1 | 0.845 | 0.041464 | 0.004027 | 0.883 | 26.842386 | 26.968699 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.0 | 6.727 | 0.0 | -1 | 1 | 0.050 | 0.0 | 0.239 | 0.239 | See | See |
| 3 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.0 | 6.786 | 0.0 | -1 | 5 | 0.049 | 0.0 | 0.239 | 0.239 | See | See |
| 6 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.0 | 6.916 | 0.0 | 1 | 100 | 0.049 | 0.0 | 0.234 | 0.234 | See | See |
| 9 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.0 | 6.883 | 0.0 | -1 | 100 | 0.049 | 0.0 | 0.235 | 0.235 | See | See |
| 12 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.0 | 6.911 | 0.0 | 1 | 5 | 0.049 | 0.0 | 0.235 | 0.235 | See | See |
| 15 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.0 | 6.915 | 0.0 | 1 | 1 | 0.050 | 0.0 | 0.233 | 0.233 | See | See |
| 18 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.0 | 0.315 | 0.0 | -1 | 1 | 0.010 | 0.0 | 0.513 | 0.513 | See | See |
| 21 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.0 | 0.317 | 0.0 | -1 | 5 | 0.010 | 0.0 | 0.512 | 0.512 | See | See |
| 24 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.0 | 0.317 | 0.0 | 1 | 100 | 0.010 | 0.0 | 0.514 | 0.514 | See | See |
| 27 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.0 | 0.319 | 0.0 | -1 | 100 | 0.010 | 0.0 | 0.504 | 0.504 | See | See |
| 30 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.0 | 0.318 | 0.0 | 1 | 5 | 0.010 | 0.0 | 0.513 | 0.513 | See | See |
| 33 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.0 | 0.313 | 0.0 | 1 | 1 | 0.010 | 0.0 | 0.513 | 0.513 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.017 | 0.041 | 0.000 | 0.002 | -1 | 1 | 0.227 | 0.001 | 8.894 | 8.894 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.003 | 0.000 | 0.023 | -1 | 1 | 0.009 | 0.000 | 2.630 | 2.630 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 3.106 | 0.046 | 0.000 | 0.003 | -1 | 5 | 0.226 | 0.001 | 13.742 | 13.742 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.025 | 0.002 | 0.000 | 0.025 | -1 | 5 | 0.009 | 0.000 | 2.785 | 2.786 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.384 | 0.005 | 0.000 | 0.002 | 1 | 100 | 0.229 | 0.003 | 10.400 | 10.400 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.021 | 0.000 | 0.000 | 0.021 | 1 | 100 | 0.009 | 0.000 | 2.320 | 2.322 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 3.119 | 0.050 | 0.000 | 0.003 | -1 | 100 | 0.285 | 0.013 | 10.952 | 10.963 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.026 | 0.004 | 0.000 | 0.026 | -1 | 100 | 0.010 | 0.000 | 2.527 | 2.529 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.375 | 0.005 | 0.000 | 0.002 | 1 | 5 | 0.282 | 0.001 | 8.407 | 8.407 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.020 | 0.000 | 0.000 | 0.020 | 1 | 5 | 0.010 | 0.002 | 1.973 | 2.014 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.252 | 0.016 | 0.001 | 0.001 | 1 | 1 | 0.230 | 0.001 | 5.444 | 5.444 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.019 | 0.000 | 0.000 | 0.019 | 1 | 1 | 0.009 | 0.000 | 2.210 | 2.211 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.744 | 0.032 | 0.000 | 0.002 | -1 | 1 | 0.037 | 0.000 | 47.682 | 47.683 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.008 | 0.002 | 0.000 | 0.008 | -1 | 1 | 0.001 | 0.000 | 8.861 | 8.907 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.964 | 0.022 | 0.000 | 0.003 | -1 | 5 | 0.037 | 0.000 | 80.994 | 80.995 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.011 | 0.005 | 0.000 | 0.011 | -1 | 5 | 0.001 | 0.000 | 11.624 | 11.658 | See | See |
| 25 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.311 | 0.002 | 0.000 | 0.002 | 1 | 100 | 0.038 | 0.000 | 60.352 | 60.352 | See | See |
| 26 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.004 | 0.000 | 0.000 | 0.004 | 1 | 100 | 0.001 | 0.000 | 3.899 | 3.929 | See | See |
| 28 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.991 | 0.038 | 0.000 | 0.003 | -1 | 100 | 0.085 | 0.000 | 34.993 | 34.993 | See | See |
| 29 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.010 | 0.003 | 0.000 | 0.010 | -1 | 100 | 0.001 | 0.000 | 10.190 | 10.239 | See | See |
| 31 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.337 | 0.027 | 0.000 | 0.002 | 1 | 5 | 0.086 | 0.003 | 27.020 | 27.035 | See | See |
| 32 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.004 | 0.000 | 0.000 | 0.004 | 1 | 5 | 0.001 | 0.000 | 3.484 | 3.501 | See | See |
| 34 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.113 | 0.007 | 0.000 | 0.001 | 1 | 1 | 0.041 | 0.004 | 26.842 | 26.969 | See | See |
| 35 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 1 | 0.001 | 0.000 | 2.293 | 2.305 | See | See |
KNeighborsClassifier_kd_tree¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | function | diff_accuracy_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 0.011 | 1000000 | 1000 | 10 | 1.699014 | 0.008849 | NaN | 0.000047 | 0.001699 | kd_tree | 1 | 5 | 0.975 | 0.110405 | 0.001272 | 0.964 | 15.388909 | 15.389930 |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.002 | 1000000 | 1000 | 10 | 0.967488 | 0.011364 | NaN | 0.000083 | 0.000967 | kd_tree | -1 | 5 | 0.975 | 0.588889 | 0.010649 | 0.973 | 1.642905 | 1.643174 |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.011 | 1000000 | 1000 | 10 | 0.891906 | 0.015064 | NaN | 0.000090 | 0.000892 | kd_tree | 1 | 1 | 0.964 | 0.195108 | 0.002086 | 0.975 | 4.571348 | 4.571609 |
| 13 | KNeighborsClassifier_kd_tree | predict | 0.002 | 1000000 | 1000 | 10 | 5.389894 | 0.058023 | NaN | 0.000015 | 0.005390 | kd_tree | 1 | 100 | 0.973 | 0.203053 | 0.002403 | 0.975 | 26.544230 | 26.546089 |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.028 | 1000 | 1000 | 2 | 0.022982 | 0.000167 | NaN | 0.000696 | 0.000023 | kd_tree | 1 | 5 | 0.923 | 0.000513 | 0.000117 | 0.895 | 44.772734 | 45.921049 |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.004 | 1000 | 1000 | 2 | 0.025739 | 0.000489 | NaN | 0.000622 | 0.000026 | kd_tree | -1 | 5 | 0.923 | 0.005467 | 0.000134 | 0.919 | 4.708290 | 4.709702 |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.028 | 1000 | 1000 | 2 | 0.021302 | 0.000252 | NaN | 0.000751 | 0.000021 | kd_tree | 1 | 1 | 0.895 | 0.000914 | 0.000136 | 0.923 | 23.298220 | 23.553737 |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.004 | 1000 | 1000 | 2 | 0.039018 | 0.000268 | NaN | 0.000410 | 0.000039 | kd_tree | 1 | 100 | 0.919 | 0.000862 | 0.000168 | 0.923 | 45.241585 | 46.088950 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.599 | 0.045 | 0.022 | 0.0 | 1 | 5 | 0.822 | 0.008 | 4.381 | 4.381 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.126 | 0.068 | 0.019 | 0.0 | -1 | 5 | 0.815 | 0.012 | 5.060 | 5.060 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.038 | 0.068 | 0.020 | 0.0 | -1 | 1 | 0.803 | 0.013 | 5.028 | 5.029 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.017 | 0.079 | 0.020 | 0.0 | 1 | 1 | 0.781 | 0.005 | 5.142 | 5.142 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.268 | 0.045 | 0.019 | 0.0 | 1 | 100 | 0.827 | 0.039 | 5.161 | 5.167 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.053 | 0.063 | 0.020 | 0.0 | -1 | 100 | 0.793 | 0.007 | 5.113 | 5.113 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.024 | 0.0 | 1 | 5 | 0.009 | 0.012 | 0.077 | 0.132 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.026 | 0.0 | -1 | 5 | 0.002 | 0.002 | 0.273 | 0.359 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.026 | 0.0 | -1 | 1 | 0.003 | 0.002 | 0.220 | 0.260 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.024 | 0.0 | 1 | 1 | 0.001 | 0.000 | 0.550 | 0.552 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.025 | 0.0 | 1 | 100 | 0.001 | 0.000 | 0.543 | 0.548 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.026 | 0.0 | -1 | 100 | 0.001 | 0.000 | 0.560 | 0.563 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.699 | 0.009 | 0.000 | 0.002 | 1 | 5 | 0.110 | 0.001 | 15.389 | 15.390 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 5 | 0.000 | 0.000 | 5.685 | 6.047 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.967 | 0.011 | 0.000 | 0.001 | -1 | 5 | 0.589 | 0.011 | 1.643 | 1.643 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 5 | 0.001 | 0.000 | 4.868 | 5.049 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.512 | 0.007 | 0.000 | 0.001 | -1 | 1 | 0.113 | 0.002 | 4.543 | 4.544 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.000 | 0.000 | 0.003 | -1 | 1 | 0.000 | 0.000 | 10.173 | 11.062 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.892 | 0.015 | 0.000 | 0.001 | 1 | 1 | 0.195 | 0.002 | 4.571 | 4.572 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 4.452 | 4.717 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 5.390 | 0.058 | 0.000 | 0.005 | 1 | 100 | 0.203 | 0.002 | 26.544 | 26.546 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.004 | 0.001 | 0.000 | 0.004 | 1 | 100 | 0.000 | 0.000 | 11.128 | 11.677 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2.928 | 0.024 | 0.000 | 0.003 | -1 | 100 | 0.580 | 0.003 | 5.050 | 5.050 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.005 | 0.001 | 0.000 | 0.005 | -1 | 100 | 0.001 | 0.000 | 8.542 | 8.825 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.023 | 0.000 | 0.001 | 0.000 | 1 | 5 | 0.001 | 0.000 | 44.773 | 45.921 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 0.000 | 0.000 | 5.193 | 6.745 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.026 | 0.000 | 0.001 | 0.000 | -1 | 5 | 0.005 | 0.000 | 4.708 | 4.710 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 5 | 0.000 | 0.000 | 17.261 | 20.874 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.024 | 0.000 | 0.001 | 0.000 | -1 | 1 | 0.001 | 0.000 | 42.358 | 43.530 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 1 | 0.000 | 0.000 | 21.264 | 26.307 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.021 | 0.000 | 0.001 | 0.000 | 1 | 1 | 0.001 | 0.000 | 23.298 | 23.554 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 5.626 | 6.946 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.039 | 0.000 | 0.000 | 0.000 | 1 | 100 | 0.001 | 0.000 | 45.242 | 46.089 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 100 | 0.000 | 0.000 | 5.644 | 6.923 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.040 | 0.000 | 0.000 | 0.000 | -1 | 100 | 0.006 | 0.000 | 7.235 | 7.250 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 100 | 0.000 | 0.000 | 18.322 | 22.195 | See | See |
KMeans_tall¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.654 | 0.006 | 30 | 0.024 | 0.0 | k-means++ | 0.505 | 0.038 | 1.295 | 1.298 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.572 | 0.003 | 30 | 0.028 | 0.0 | random | 0.543 | 0.032 | 1.053 | 1.055 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 6.768 | 0.056 | 30 | 0.118 | 0.0 | k-means++ | 2.936 | 0.009 | 2.305 | 2.305 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 6.466 | 0.031 | 30 | 0.124 | 0.0 | random | 3.097 | 0.014 | 2.088 | 2.088 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.362 | 1.08 | 30 | 0.000 | 0.000 | k-means++ | 0.0 | 0.0 | 2024.555 | 2262.061 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.00 | 30 | 0.000 | 0.002 | k-means++ | 0.0 | 0.0 | 12.041 | 14.273 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.00 | 30 | 0.010 | 0.000 | random | 0.0 | 0.0 | 9.275 | 10.607 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.002 | 0.00 | 30 | 0.000 | 0.002 | random | 0.0 | 0.0 | 12.030 | 14.375 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.00 | 30 | 0.403 | 0.000 | k-means++ | 0.0 | 0.0 | 6.428 | 7.155 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.00 | 30 | 0.001 | 0.002 | k-means++ | 0.0 | 0.0 | 10.103 | 11.591 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.00 | 30 | 0.399 | 0.000 | random | 0.0 | 0.0 | 6.216 | 6.599 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.002 | 0.00 | 30 | 0.001 | 0.002 | random | 0.0 | 0.0 | 10.636 | 12.186 | See | See |
KMeans_short¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | diff_adjusted_rand_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | init | max_iter | n_clusters | n_init | tol | adjusted_rand_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | adjusted_rand_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 4 | KMeans_short | predict | 0.001559 | 10000 | 1000 | 2 | 0.002192 | 0.000116 | 20 | 0.007300 | 0.000002 | full | random | 20 | 300 | 1 | 1.000000e-16 | 0.000139 | 0.000631 | 0.000106 | 0.001698 | 3.473654 | 3.521957 |
| 7 | KMeans_short | predict | 0.006417 | 10000 | 1000 | 100 | 0.003105 | 0.000169 | 20 | 0.257631 | 0.000003 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.301489 | 0.001320 | 0.000135 | 0.295073 | 2.352137 | 2.364369 |
| 10 | KMeans_short | predict | 0.039683 | 10000 | 1000 | 100 | 0.003116 | 0.000141 | 20 | 0.256778 | 0.000003 | full | random | 20 | 300 | 1 | 1.000000e-16 | 0.259606 | 0.001261 | 0.000130 | 0.299288 | 2.469968 | 2.483114 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 0.289 | 0.003 | 20 | 0.001 | 0.0 | k-means++ | 0.102 | 0.001 | 2.839 | 2.840 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 0.103 | 0.000 | 20 | 0.002 | 0.0 | random | 0.035 | 0.000 | 2.968 | 2.969 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 0.755 | 0.007 | 20 | 0.011 | 0.0 | k-means++ | 0.391 | 0.004 | 1.931 | 1.931 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 0.260 | 0.004 | 20 | 0.031 | 0.0 | random | 0.145 | 0.003 | 1.796 | 1.796 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.007 | 0.000 | k-means++ | 0.001 | 0.0 | 3.499 | 3.541 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.0 | 20 | 0.000 | 0.002 | k-means++ | 0.000 | 0.0 | 11.614 | 13.640 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.007 | 0.000 | random | 0.001 | 0.0 | 3.474 | 3.522 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 0.002 | 0.0 | 20 | 0.000 | 0.002 | random | 0.000 | 0.0 | 11.627 | 13.588 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.0 | 20 | 0.258 | 0.000 | k-means++ | 0.001 | 0.0 | 2.352 | 2.364 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.0 | 20 | 0.000 | 0.002 | k-means++ | 0.000 | 0.0 | 8.590 | 9.413 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.0 | 20 | 0.257 | 0.000 | random | 0.001 | 0.0 | 2.470 | 2.483 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 0.002 | 0.0 | 20 | 0.000 | 0.002 | random | 0.000 | 0.0 | 8.585 | 9.413 | See | See |
LogisticRegression¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | 11.985 | 0.045 | [20] | 0.067 | 0.000 | 2.092 | 0.008 | 5.730 | 5.730 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | 0.824 | 0.017 | [27] | 0.097 | 0.001 | 0.774 | 0.036 | 1.064 | 1.065 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 0.000 | 0.0 | [20] | 2.364 | 0.0 | 0.000 | 0.0 | 0.797 | 0.829 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | 0.000 | 0.0 | [20] | 0.010 | 0.0 | 0.000 | 0.0 | 0.406 | 0.452 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 0.002 | 0.0 | [27] | 4.164 | 0.0 | 0.003 | 0.0 | 0.583 | 0.585 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | 0.000 | 0.0 | [27] | 0.774 | 0.0 | 0.001 | 0.0 | 0.128 | 0.131 | See | See |
Ridge¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | 0.200 | 0.001 | 0.400 | 0.0 | 0.206 | 0.001 | 0.971 | 0.971 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | 1.211 | 0.023 | 0.661 | 0.0 | 0.254 | 0.002 | 4.771 | 4.771 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 0.01 | 0.0 | 7.913 | 0.0 | 0.017 | 0.0 | 0.600 | 0.600 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | 0.00 | 0.0 | 1.011 | 0.0 | 0.000 | 0.0 | 0.565 | 0.622 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | 0.00 | 0.0 | 4.531 | 0.0 | 0.000 | 0.0 | 0.652 | 0.701 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | 0.00 | 0.0 | 0.012 | 0.0 | 0.000 | 0.0 | 0.670 | 0.771 | See | See |